Capital One Services, LLC

James Zarakas

Tyler Sylvain Locke

Adam R Koeppel

Molly Elizabeth Johnson

Adam Vukich

David Kelly Wurmfeld

Kevin Patrick Kelly

Saleem Ahmed Sangi

George Bergeron

Theodore Markson

Robert T Perry

Jeffrey Rule

Kevin Grant Osborn

Brennon York

Rajko Ilincic

Kevan Emmott

Karla M Escalante

Brian Briggman

Joshua S Edwards

Abdelkader M'Hamed Benkreira

Eric Medin

Jonathan Bodner

Srinivasa Chigurupati

Sarah Jane Cunningham

William Carroll

Mohamed Lafeer

Adam Koeppel

Mark C Dupuis

Kevin Kelly

David Wurmfeld

Tyler Locke

A secure smart card is described. The smart card can include a processor, a memory and a transceiver. The smart card can communicate with various terminals and store a digital signature and other information on the card. Another terminal can validate the information stored on the smart card using the digital signature. In certain embodiments, the terminal can also validate the information by using a blockchain. The advanced design of the smart card obviates the need for a network connection.

System and apparatus for encrypted data collection using RFID cards

A system for securely updating an electronic transaction card held by an account holder with an additional account and/or account data is described. A dynamic transaction card may be securely updated with an additional account by using pre-stored shell data and/or inactive data, whereby the pre-stored shell data may be populated using data received from an issuer system and/or the inactive data may be activated via an activation signal received from a mobile device.

System, method, and apparatus for updating an existing dynamic transaction card

A fuel price determination system may receive transaction data identifying purchases, made with transaction cards and mobile transaction card applications of client devices, of fuel at fuel stations. The fuel price determination system may receive location data identifying locations associated with users of the client devices and the transaction cards, and user history data associated with prior purchases of fuel at fuel stations by the users. The fuel price determination system may process the transaction data, location data, and user history data, with a machine learning model, to determine fuel prices at the fuel stations. The fuel price determination system may determine a ranked list of particular fuel stations in a geographical area based on the fuel prices and populate, based on the location data and the ranked list, a map to identify the particular fuel stations and the fuel prices at the particular fuel stations.

Utilizing machine learning and transaction data to determine fuel prices at fuel stations

The present disclosure describes a smart card that determines a context associated with the smart card and displays information based on the determined context. The smart card may determine a location of the smart card. Based on the determined location, the smart card may retrieve a list of establishments. The list of establishments may be used to determine a context, for example, based on information related to the establishments, historical information, user information, etc. Once the context is determined, the smart card may select information to display on the smart card. By limiting the information displayed on the smart card, the smart card may limit what can be captured by bad actors, thereby improving the security of the smart cards.

Dynamically displaying contextual information on a smart card

A device may include a processor, a wireless transceiver in communication with the processor, and a non-transitory memory. The memory may store instructions that, when executed by the processor, cause the processor to perform processing. The processing may include receiving a command configured to be executed by an external user device. The external user device and the user device may be members of a network of trust. The processing may include detecting, by the wireless transceiver, a plurality of member devices of the network of trust in communication range of the device. The processing may include sending, by the wireless transceiver, the command to each of the plurality of member devices.

Remote commands using network of trust

A multi-function transaction card may receive, from shelf sensors, first data indicating that items have been removed from shelves by a customer of a merchant, and may receive, from shopping cart sensors, second data indicating that the items have been placed in a shopping cart. The multi-function transaction card may receive, based on the first data and the second data, item data identifying the items placed in the shopping cart, wherein the item data is received from price tags of the items. The multi-function transaction card may store the item data, and may provide, to a transaction terminal of the merchant, the item data identifying the items and customer data identifying the customer. The multi-function transaction card may receive, from the transaction terminal, transaction data identifying a transaction that charges the multi-function transaction card for a total cost of the items.

Utilizing a multi-function transaction card to capture item data and enable expedited checkout for purchased items

A fraud detection platform may receive transaction data relating to a transaction conducted by a user with a transaction card. The fraud detection platform may receive, from a biometric sensor of the transaction card, biometric data relating to one or more biometric characteristics of the user during the transaction. The fraud detection platform may receive, from an accelerometer of the transaction card, card movement data relating to a measure of shaking of the transaction card by the user during the transaction. The fraud detection platform may process the transaction data, the biometric data, and the card movement data, with a fraud detection model, to determine a fraud score associated with the transaction. The fraud detection platform may perform one or more actions based on the fraud score.

Utilizing card movement data to identify fraudulent transactions

An EMV enabled terminal may communicate transaction related information to a user via a standard user interface of the terminal, for example, within a user interface displayed on a display screen of the terminal. The transaction related information may be spoken out loud to the user by the terminal. However, users with visual, audio, or other physical impairments may be unable to access the display of the terminal, view the displayed information, or hear the spoken information. Systems and methods disclosed herein communicate transaction related information via an alternate user interface. Instead of relying on the standard user interface related communications, information about the status of a transaction or transaction related information may be determined based on monitoring and evaluating the communications between an EMV secure element of a dynamic transaction card and the terminal via a contact connection.

EMV secure chip communications

In a method of facilitating encrypted communications between a transmitting system having a unique identifier and a receiving system, a key generation system generates at least one encryption master key for use with the unique identifier and an encryption algorithm to produce a transmitting system-unique encryption key. The key generation system also generates a shared secret master key for use with the unique identifier and a second encryption algorithm to produce a shared secret value. The at least one encryption master key and the shared secret master key are then stored in an encryption information database. The key generation system transmits the at least one encryption master key and shared secret information to the transmitting system and transmits the at least one encryption master key, the shared secret master key and the unique identifier to the receiving data processing system.

Parallel secret salt generation and authentication for encrypted communication

A device may receive, from a client device of a customer, item data identifying a price of an item and customer data identifying the customer, where the item data may be received by a transaction card from a price tag of the item. The device may receive price data identifying prices associated with multiple items and other data identifying locations, availabilities, and terms of the multiple items, and may process the item data, the price data, and the other data, with a machine learning model, to identify an optimal price for the item. The device may provide, to the client device, data identifying the optimal price and data identifying a merchant associated with the optimal price, and may receive transaction data identifying the item, the optimal price, and the merchant when the customer purchases the item. The device may perform actions based on the transaction data.

Utilizing machine learning and a smart transaction card to automatically identify optimal prices and rebates for items during in-person shopping

A transaction card includes a near-field communication (NFC) component, a security component, a wireless component, one or more memories, and one or more processors communicatively coupled to the one or more memories. The device receives a signal from a user device attempting to access a secure application, and energizes the NFC component based on the signal received from the user device. The device causes the security component to generate an encrypted code based on the NFC component being energized, and provides, via the security component, the encrypted code to the wireless component. The device provides, via the wireless component, the encrypted code to the user device to permit the user device to utilize the encrypted code as authentication for accessing the secure application.

Utilizing a transaction card to provide secondary authentication for accessing a secure application with a user device

A transaction card may power on the transaction card using electric current induced from an interaction of the transaction card with an electromagnetic field. The transaction card may establish a communication with a device. The communication may indicate that the transaction card has powered. The transaction card may receive, from the device, a set of instructions to configure a set of applets on the transaction card after notifying the device that the transaction card has powered on. The set of applets to be configured may be related to completing one or more different transactions. The set of applets to be configured may be different than another set of applets already configured on the transaction card. The transaction card may configure the set of applets on the transaction card according to the set of instructions after receiving the set of instructions.

Configuring a set of applets on a battery-less transaction card

Disclosed embodiments describe a system for completing a transaction using an electronic transaction card by receiving, from a user device executing a software application, a selection of a first account function associated with a financial transaction; determining that the account function requires user verification; detecting, via a motion detection component, a motion pattern performed on the electronic transaction card by the user; authenticating an identity of the user, by the electronic transaction card, based on the detected motion pattern; and completing, by the user device, the financial transaction.

Systems and methods for active signature detection

In some implementations, a transaction card may receive transaction data from a transaction terminal based on initiation of a transaction with the transaction terminal; generate a tokenized primary account number, for use with the transaction, based on the transaction data and an actual primary account number of the transaction card; and transmit the tokenized primary account number to the transaction terminal for processing the transaction.

Tokenizing a primary account number prior to transmission to a terminal

A user profile scoring platform may analyze a transaction log of a transaction account of a user to determine, based on transactions of the transaction log, a qualification status of the user, wherein the qualification status indicates that a characteristic of the user satisfies a threshold qualification metric. The user profile scoring platform may determine, based on the qualification status, a transaction-based score associated with the user, wherein the transaction-based score is determined using a transaction log analysis model. The user profile scoring platform may obtain, based on receiving the access information, a user score associated with a user transaction history that is associated with a plurality of transaction accounts that are associated with the user and different from the transaction account. The user profile scoring platform may perform an action based on the transaction-based score and the user score.

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Centreville, VA, United States of America

James Zarakas